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  • 1
    In: Kidney International, Elsevier BV, Vol. 89, No. 5 ( 2016-05), p. 1144-1152
    Type of Medium: Online Resource
    ISSN: 0085-2538
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2016
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  • 2
    In: Nature Genetics, Springer Science and Business Media LLC, Vol. 49, No. 8 ( 2017-8), p. 1211-1218
    Type of Medium: Online Resource
    ISSN: 1061-4036 , 1546-1718
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2017
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  • 3
    In: Nature Genetics, Springer Science and Business Media LLC, Vol. 51, No. 4 ( 2019-4), p. 694-704
    Type of Medium: Online Resource
    ISSN: 1061-4036 , 1546-1718
    RVK:
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
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  • 4
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 3671-3671
    Abstract: Whole-genome sequencing (WGS) is invaluable for investigating genetic abnormalities contributing to the initiation, progression and long-term clinical outcome of pediatric cancer. St. Jude Cloud (https://www.stjude.cloud/) hosts 10,000 (10K) harmonized WGS samples generated from: 1) St. Jude/Washington University Pediatric Cancer Genome Project, 2) the Genomes for Kids Clinical Trial, 3) the St. Jude Lifetime Cohort Study, and 4) the Childhood Cancer Survivor Study. To enable on-the-cloud discovery and eliminate the need for data download, we developed GenomePaint, an interactive genomics browser, to explore the somatic and germline variants of the 10K genomes with rich annotation. Germline variants in cancer predisposition genes were annotated for pathogenicity. Using GenomePaint, users can compare pathogenic variants from a locus of interest across multiple cancers or test for association of a germline variant with a specific cancer type on the fly. By matching germline variants to somatic mutation hotspots from www.cancerhotspots.org, we annotated potential germline mosaic mutations including IDH1 R132H, FBXW7 R465C, and KRAS A146T. For noncoding variants, we investigated overlap with ATAC and DNase peaks in 50 cancer cell lines along with transcription factor motif change predictions. These features will enable exploration of the functional impact of genetic variations with potential clinical status such as genetic risk for a specific cancer type, genetic association with age of onset, or development of subsequent malignancies for pediatric cancer survivors. GenomePaint also provides an integrated view of somatic SNV/indel, copy number variation, loss-of-heterozygosity, structural variation, and gene fusion. These are shown together with tumor gene expression at the single tumor level. GenomePaint also presents allele-specific expression (ASE) and outlier expression as an indicator for assessing dysfunction of regulatory regions caused by genomic variants. Cloud-based on-the-fly ASE analysis is also available for user’s samples with paired DNA and RNA sequencing results. Such gene expression integration will drive novel insights about the functional aspects of somatic coding and noncoding mutations in pediatric cancer. The innovative visualization of whole-genome sequencing data generated from 10K pediatric cancer patients on the St. Jude Cloud enables genomic discovery by scientists and clinicians through exploration of this unprecedented resource. Citation Format: Xin Zhou, Clay Mcleod, Scott Newman, Zhaoming Wang, Michael Rusch, Kirby Birch, Michael Macias, Jobin Sunny, Gang Wu, Jian Wang, Edgar Sioson, Shaohua Lei, Robert J. Michael, Aman Patel, Michael N. Edmonson, Stephen V. Rice, Andrew Frantz, Ed Suh, Keith Perry, Carmen Wilson, Leslie L. Robinson, Yutaka Yasui, Kim E. Nichols, Gregory T. Armstrong, James R. Downing, Jinghui Zhang. Visualize 10,000 whole-genomes from pediatric cancer patients on St. Jude Cloud [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3671.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
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  • 5
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 13_Supplement ( 2018-07-01), p. 922-922
    Abstract: While whole-genome (WGS), whole-exome (WES), and RNA-Seq data of patient samples are key resources for the development of precision medicine, major computing infrastructure is typically required to use them effectively. The St Jude Cloud (SJCloud, https://stjude.cloud), built in collaboration with DNAnexus and Microsoft, aims to remove this barrier by sharing genomic sequencing data generated at St Jude Children's Research Hospital, making complex bioinformatics pipelines easily accessible, and providing intuitive visualizations for data mining in the cloud. Over 5000 WGS, 6000 WES and 1500 RNA-Seq from & gt;5,000 pediatric cancer patients mapped to the latest reference genome are securely available in SJCloud. These data were generated from three St Jude-funded genomic initiatives: the Pediatric Cancer Genome Project (PCGP), the St Jude Life Genome Project, and the Genomes for Kids Clinical Trial. SJCloud hosts BAM files, coding and non-coding somatic and germline SNVs and indels, copy number (CNV) and structural alterations (SV). Non-identifiable data (e.g. somatic alterations, genotype frequency, cancer diagnosis and demographics) can be viewed immediately using our interactive genome browser, while raw data and individual genotype access requires a simple online approval. Data synchronization and visualization enables novel discoveries by non-bioinformaticians. For example, a genomic view of the TERT locus shows enrichment of CNVs and SVs in neuroblastoma (NBL), consistent with reports of activation via rearrangement. The same view also shows a somatic promoter mutation, C228T, in one NBL; such mutations have not been reported in primary samples to our knowledge. This integrated view across somatic mutation types enables evaluation of the diverse genetic mechanisms deregulating cancer genes. SJCloud also facilitates data re-analysis. We ported the “MutationalPatterns” R package (Blokzijl et al. 2017) to the cloud to elucidate major mutational signatures in & gt;500,000 PCGP WGS somatic variants. Inclusion of non-coding mutations was critical as the low number of exonic mutations in some pediatric cancers is insufficient for robust analysis. A surprising finding was a signature consistent with ultraviolet-induced DNA damage in a subset of B-acute lymphoblastic leukemia. End-to-end workflows to detect gene fusions, predict neoepitopes, classify mutations, process ChIP-seq, and identify differentially expressed genes are also freely accessible. By integrating analytic tools with the world's largest set of pediatric genomics data, SJCloud enables data sharing and mining, innovative genomic analysis, and development of new analytic methods. We anticipate that in 2019 we will host data from over 10,000 pediatric cancer patients, and we are actively exploring approaches to make this a federated data repository capable of interchange with the global pediatric cancer research community. Citation Format: Scott Newman, Xin Zhou, Clay McLeod, Michael Rusch, Gang Wu, Edgar Sioson, Shuoguo Wang, J. Robert Michael, Aman Patel, Michael N. Edmonson, Andrew Frantz, Ti-Cheng Chang, Yongjin Li, Robert I. Davidson, Singer Ma, Irina McGuire, Nedra Robison, Xing Tang, Lance Palmer, Ed Suh, Leigh Tanner, James McMurry, Keith Perry, Zhaoming Wang, Carmen Wilson, Yong Cheng, Mitch Weiss, Leslie L. Robison, Yutaka Yasui, Kim E. Nichols, David W. Ellison, James R. Downing, Jinghui Zhang. Access, visualize and analyze 5,000 whole-genomes from pediatric cancer patients on St. Jude Cloud [abstract]. In: Proceedings of the Amer ican Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 922.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2018
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  • 6
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 2872-2872
    Abstract: Acute lymphoblastic leukemia (ALL) is a leading cause of cancer-associated death in children. To study the mechanisms of drug resistance in ALL, we performed whole-genome sequencing of diagnosis-relapse-germline trios from 103 Chinese patients and ultra-deep sequencing of 208 serial bone marrow samples from 17 of them. Relapse-specific somatic alterations were enriched in 12 genes (NR3C1, NR3C2, TP53, NT5C2, FPGS, CREBBP, MSH2, MSH6, PMS2, WHSC1, PRPS1, and PRPS2), which were predominantly involved in response to thiopurines, glucocorticoids, methotrexate, and other drugs. Four lines of evidence indicate that these resistance mutations frequently developed during treatment, rather than pre-existing at diagnosis. First, two novel, relapse-specific mutational signatures (novel signatures 1 and 2), most likely caused by chemotherapeutic regimens, were detected in 15% and 14% of relapsed cases, respectively. Drug resistance mutations frequently appeared at novel signature-associated trinucleotide contexts, indicating that chemotherapy may directly cause drug resistance mutations in ALL. The signatures were validated in NCI TARGET relapsed ALL samples, 2% and 23% of which harbored novel signatures 1 and 2, respectively. The varying signature prevalence between cohorts may reflect treatment differences. The novel signatures were not detected in & gt;2,000 adult cancers from the PCAWG study. Novel signature 1 induced C & gt;G transversions, particularly at GCC and TCT trinucleotides, and showed transcription-strand bias indicating guanine adducts. Novel signature 2 favored C & gt;T and C & gt;G mutations at CCG, and correlated with relapse-specific dinucleotide variants and structural variants, indicating an agent causing multiple mutation types. The drugs inducing these novel signatures are being explored in vitro. Second, mathematical modeling using growth curves of drug-resistant ALL indicated that drug resistance mutations occur, in some cases, long after diagnosis, during active treatment. Third, some patients acquired multiple drug resistance mutations sequentially through successive relapses, a finding inconsistent with their pre-existence at diagnosis. Indeed, 20% of relapses had multiple drug resistance mutations targeting different drug classes. Fourth, most relapsed ALLs derived from a subclone detected at diagnosis, which then evolved additional mutations, including drug resistance mutations, not detectable at diagnosis using 2000X targeted sequencing. Drug resistance mutations were often subclonal at relapse, suggesting later appearance. Together these data indicate that fully drug-resistant clones may not necessarily pre-exist at diagnosis in ALL, but may be acquired later during treatment. Thus, early intensive or targeted treatment strategies in slow responders may forestall the subsequent development of drug resistance mutations. Citation Format: Benshang Li, Samuel W. Brady, Xiaotu Ma, Shuhong Shen, Yingchi Zhang, Yongjin Li, Yu Liu, Ningling Wang, Diane Flasch, Matthew Myers, Heather Mulder, Lixia Ding, Yanling Lu, Liqing Tian, Kohei Hagiwara, Ke Xu, Edgar Sioson, Tianyi Wang, Liu Yang, Jie Zhao, Hui Zhang, Ying Shao, Hongye Sun, Lele Sun, Jiaoyang Cai, Ting-Nien Lin, Lijuan Du, Fan Yang, Michael Rusch, Michael Edmonson, John Easton, Xiaofan Zhu, Jingliao Zhang, Cheng Cheng, Benjamin Raphael, Jingyan Tang, James Downing, Bin-Bing Zhou, Ching-Hon Pui, Jun Yang, Jinghui Zhang. Acquisition of drug resistance mutations during chemotherapy treatment in pediatric acute lymphoblastic leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2872.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
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  • 7
    In: Nature, Springer Science and Business Media LLC, Vol. 555, No. 7696 ( 2018-03-15), p. 371-376
    Abstract: Analysis of molecular aberrations across multiple cancer types, known as pan-cancer analysis, identifies commonalities and differences in key biological processes that are dysregulated in cancer cells from diverse lineages. Pan-cancer analyses have been performed for adult 1,2,3,4 but not paediatric cancers, which commonly occur in developing mesodermic rather than adult epithelial tissues 5 . Here we present a pan-cancer study of somatic alterations, including single nucleotide variants, small insertions or deletions, structural variations, copy number alterations, gene fusions and internal tandem duplications in 1,699 paediatric leukaemias and solid tumours across six histotypes, with whole-genome, whole-exome and transcriptome sequencing data processed under a uniform analytical framework. We report 142 driver genes in paediatric cancers, of which only 45% match those found in adult pan-cancer studies; copy number alterations and structural variants constituted the majority (62%) of events. Eleven genome-wide mutational signatures were identified, including one attributed to ultraviolet-light exposure in eight aneuploid leukaemias. Transcription of the mutant allele was detectable for 34% of protein-coding mutations, and 20% exhibited allele-specific expression. These data provide a comprehensive genomic architecture for paediatric cancers and emphasize the need for paediatric cancer-specific development of precision therapies.
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2018
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    SSG: 11
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